Background: Core affect is defined as the most general affective construct consciously accessible that is experienced constantly. It can be experienced as free-floating (mood) or related to prototypical emotional episodes. The aim of this study was to examine the influence of pleasant and unpleasant core affect on cyclo-ergometer endurance performance. Specifically, we considered the influence of pleasant and unpleasant core affect on performance outcomes (i.e., time to task completion) and rate of perceived exertion (RPE; Borg Scale, category ratio-10) collected during the task.
Methods: Thirty-one participants aged 20-28 years were recruited. Core affect was randomly elicited by 2 sets of pleasant and unpleasant pictures chosen from the international affective picture system. Pictures were displayed to participants during a cyclo-ergometer performance in 2 days in a counterbalanced order. RPE was collected every minute to detect volunteers' exhaustion.
Results: The study sample was split into 2 groups. Group 1 comprised participants who performed better with pleasant core affect, whereas Group 2 included participants who performed better with unpleasant core affect. Mixed between-within subjects analysis of variance revealed a significant 2 (group) × 2 (condition) × 5 (isotime) interaction (p = 0.002, η = 0.158). Post hoc comparisons showed that participants who obtained better performance with pleasant core affect (pleasant pictures; Group 1) reported lower RPE values at 75% of time to exhaustion in a pleasant core affect condition compared to an unpleasant core affect condition. On the other hand, participants who obtained better performance with unpleasant core affect (unpleasant pictures; Group 2) reported lower RPE values at 75% and 100% of time to exhaustion in an unpleasant core affect condition.
Conclusion: Findings suggest differential effects of pleasant and unpleasant core affect on performance. Moreover, core affect was found to influence perceived exertion and performance according to participants' preferences for pleasant or unpleasant core affect.
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http://dx.doi.org/10.1016/j.jshs.2019.12.004 | DOI Listing |
Front Microbiol
December 2024
Scientific Research Institute of Systems Biology and Medicine, Moscow, Russia.
Introduction: WhiA is a conserved protein found in numerous bacteria. It consists of an HTH DNA-binding domain linked with a homing endonuclease (HEN) domain. WhiA is one of the most conserved transcription factors in reduced bacteria of the class Mollicutes.
View Article and Find Full Text PDFVertebrate vision in dim-light environments is initiated by rod photoreceptor cells that express the photopigment rhodopsin, a G-protein coupled receptor (GPCR). To ensure efficient light capture, rhodopsin is densely packed into hundreds of membrane discs that are tightly stacked within the rod-shaped outer segment compartment. Along with its role in eliciting the visual response, rhodopsin serves as both a building block necessary for proper outer segment formation as well as a trafficking guide for a few outer segment resident membrane proteins.
View Article and Find Full Text PDFMicrobes of nearly every species can form biofilms, communities of cells bound together by a self-produced matrix. It is not understood how variation at the cellular level impacts putatively beneficial, colony-level behaviors, such as cell-to-cell signaling. Here we investigate this problem with an agent-based computational model of metabolically driven electrochemical signaling in Bacillus subtilis biofilms.
View Article and Find Full Text PDFUnlabelled: Bactofilins are a recently discovered class of cytoskeletal protein, widely implicated in subcellular organization and morphogenesis in bacteria and archaea. Several lines of evidence suggest that bactofilins polymerize into filaments using a central β-helical core domain, flanked by variable N- and C-terminal domains that may be important for scaffolding and other functions. However, a systematic exploration of the characteristics of these domains has yet to be performed.
View Article and Find Full Text PDFHealth Sci Rep
January 2025
Department of Microbiology Dr D. Y. Patil Medical College, Hospital and Research Centre, Dr D. Y. Patil Vidyapeeth (Deemed-to-be-University) Pune Maharashtra India.
Background And Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment.
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